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Remote role plus broad LLM/MLOps requirements attracts many applicants despite unknown employer.
Strong LLM, MLOps, and production ML specialization moderately limits cross-industry transferability.
Explicit 6+ years plus mandatory Python, LLM, vector DB, cloud, and MLOps experience increases filter strictness.
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Design, build, and deploy AI/ML models including large language models (LLMs) and Retrieval Augmented Generation (RAG) pipelines at scale.
Develop and optimize scalable AI services and microservices using Python, REST APIs, and cloud-native technologies across Azure, AWS, or GCP.
Implement MLOps workflows including CI/CD for model lifecycle management, monitoring performance, retraining, and integration with enterprise systems.
6+ years of professional experience in Python development with ML frameworks such as PyTorch, TensorFlow, and Transformers.
Hands-on experience with large language models including OpenAI, Azure OpenAI, Anthropic, or Llama.
Proficiency with cloud platforms (Azure, AWS, GCP) and serverless computing services.
Work Experience Required: 6+ years; Notice Period: Not explicitly mentioned in the JD.
Experienced AI engineer comfortable working remotely during 2pm - 10pm time zone hours, with strong productionizing skills for AI/ML models at scale.
Operates effectively at the intersection of AI model development, MLOps, and cloud service integration with an emphasis on performance, cost, and compliance.
Demonstrated ability to collaborate with cross-functional teams including data engineering, product, and business teams while translating complex AI concepts for technical and non-technical stakeholders.